ONE // The AI Talent Arms Race Reshapes Tech Hiring

AI is becoming a prerequisite in tech hiring. Nearly one in four U.S. tech job postings in 2025 require artificial intelligence expertise, as demand for AI skills spreads beyond Silicon Valley into finance, retail, healthcare, and beyond.

By the Numbers:

• 36% of tech job postings in the information sector were AI-related in January.

• AI-related job postings across all industries have risen 68% since the release of ChatGPT in late 2022.

• Tech job listings overall declined 27% in the same period.

• AI postings now represent 1.3% of all job openings, compared to 5.4% for general tech jobs.

Zoom In:

• Wall Street and consulting firms are hunting for AI-savvy hires to integrate machine learning into risk modeling and client services.

• Retailers are seeking AI experts to refine store layouts and personalize marketing.

• Utilities are leveraging AI to assess wildfire risks, while pharmaceutical firms are applying it to computational chemistry.

• Healthcare and real estate, historically slower in tech hiring, are expanding their AI-focused roles.

What They’re Saying:

• “Companies are prioritizing AI in existing jobs, rather than creating brand-new AI roles,” said Thomas Vick of Robert Half. Cybersecurity engineers, for example, are now expected to use AI to automate threat detection.

• AI expertise is also proving recession-resistant, with firms holding onto employees with high-level AI skills even amid layoffs elsewhere.

The Bottom Line: The AI-driven job market is creating a divide: Engineers with AI fluency are commanding premium salaries and job security, while those without it face an uncertain outlook in an increasingly unforgiving market.

Source: The Wall Street Journal [hybrid paywall]

TWO // McKinsey: Leaders Lag on AI as Employees Embrace Change

AI is reshaping work, but while employees are adopting it at scale, leadership remains the biggest obstacle to its full integration. McKinsey's latest research highlights that while 92% of companies are increasing AI investments, only 1% consider themselves “mature” in AI deployment.

By the Numbers:

• 3× – Employees are using AI for a third or more of their work at three times the rate their leaders assume.

• 47% – The share of executives who admit their companies are moving too slowly on AI.

• 1.4× – Millennials are more likely than other generations to be extensively familiar with AI tools.

• 48% – Employees who rank AI training as their top need, yet half say they receive little to no support.

• 92% – Companies planning to invest more in AI over the next three years.

• 1% – Companies that believe they have reached AI maturity.

The Roadblocks:

1. Leadership Hesitation – Employees trust their companies to deploy AI responsibly but are left waiting for strategic direction.

2. Lack of Training – The top request from employees, yet largely unaddressed.

3. Unclear ROI – 87% of executives expect AI-driven revenue growth, yet most report limited impact so far.

4. Regulatory and Ethical Concerns – Employees worry about security, bias, and accuracy, while companies struggle to balance speed with responsibility.

The Bottom Line: AI represents a century-defining transformation, reshaping industries, economies, and the nature of work itself. Organizations that hesitate will lose ground to more adaptive competitors. Employees are integrating AI into their work. Leaders must now align strategies and invest in training to unlock AI’s full economic potential.

Source: McKinsey [download]

THREE // Why Your Company Needs an AI Policy, Yesterday

As artificial intelligence becomes embedded in daily operations, companies face rising risks related to security, intellectual property, regulatory compliance, and workforce management. Employers are increasingly drafting AI usage policies to establish guidelines, mitigate liabilities, and ensure responsible implementation.

Why It Matters:

• Courts, state bars, and regulators are tightening oversight on AI use, requiring transparency and safeguards, particularly in legal, HR, and financial decision-making.

• AI-driven hiring tools, if unchecked, can expose companies to bias claims and regulatory penalties.

• Many third-party AI vendors lack clear guardrails, making it imperative for businesses to set their own standards before integrating external AI solutions.

Zoom In:

• Key components of an AI policy should include:

  • Defining AI tools that are approved and restricted.

  • Clear usage boundaries to avoid data security breaches and algorithmic bias.

  • Mandatory human oversight to prevent AI from making final employment or business decisions.

  • Regular audits and training to ensure policies stay current amid rapid legal and technological shifts.

• Companies should also prepare for a fragmented regulatory landscape, with states like Colorado and Texas modeling AI laws after Europe’s strict AI Act.

What They’re Saying:

• Generic AI policies won’t cut it. Each business must tailor policies to its specific risks and industry standards.

• Transparency builds trust. Employees should understand how AI is used in their workplace to avoid unintended risks and ensure compliance.

The Bottom Line: Without proactive policies, companies risk legal exposure, reputational damage, and workforce disruptions as AI adoption accelerates. Organizations that invest in well-defined AI guidelines today will be better positioned to harness its benefits while avoiding costly pitfalls.

Source: Kelley, Bradford J., Mike Skidgel, and Alice Wang. "Considerations for Artificial Intelligence Policies in the Workplace." Littler, March 10, 2025.

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